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Analyze gravity tide signal based on ICA with PSO

机译:使用PSO分析基于ICA的重力潮汐信号

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Independent Component Analysis (ICA) is used to separate the relatively independent signals from the source. Gravity tide signal is a mixed signal which is caused by the moon and the sun, so ICA is applied to separate gravity tide signal in this paper. Because of the slowly convergence speed and local search for the target in ICA, Particle Swarm Optimization which could find target globally and quickly is proposed to search the optical target in ICA. Simulation results show that the method proposed in this paper solves the problem presented in ICA and separates gravity tide signal into three parts. Every part represents the signal which is corresponding to the theory frequencies of the harmonic component in gravity tide signal. So the method proposed in the paper can divide the signal into three parts which is corresponding to harmonic component automatically.
机译:独立分量分析(ICA)用于从源中分离相对独立的信号。重力潮汐信号是由月亮和太阳引起的混合信号,因此本文采用ICA来分离重力潮汐信号。由于ICA中收敛速度较慢,且在ICA中对目标进行局部搜索,因此提出了一种可以全局快速找到目标的粒子群优化算法,以在ICA中搜索光学目标。仿真结果表明,本文提出的方法解决了ICA中存在的问题,并将重力潮汐信号分为三个部分。每个部分代表与重力潮汐信号中谐波分量的理论频率相对应的信号。因此,本文提出的方法可以将信号自动分为与谐波分量相对应的三个部分。

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